class_docstr: NDArray trace object
  
  Parameters
  ----------
  name: str
      Name of backend. This has no meaning for the NDArray backend.
  model: Model
      If None, the model is taken from the `with` context.
  vars: list of variables
      Sampling values will be stored for these variables. If None,
      `model.unobserved_RVs` is used.
class_docstr_tok: ["NDArray","trace","object","Parameters","--","--","--","--","--","name",":","str","Name","of","backend",".","This","has","no","meaning","for","the","NDArray","backend",".","model",":","Model","If","None",",","the","model","is","taken","from","the","`","with","`","context",".","vars",":","list","of","variables","Sampling","values","will","be","stored","for","these","variables",".","If","None",",","`","model.unobserved_RVs","`","is","used","."]
docstr: Return dictionary of point values at `idx` for current chain
  with variable names as keys.
docstr_tok: ["Return","dictionary","of","point","values","at","`","idx","`","for","current","chain","with","variable","names","as","keys","."]
code: def point(self, idx) -> Dict[str, Any]:
      """Return dictionary of point values at `idx` for current chain
      with variable names as keys.
      """
      idx = int(idx)
      return {
          varname: values[idx]
          for varname, values in self.samples.items()
      }
  
file_path: pymc/pymc/backends/ndarray.py
imports: from typing import Any, Dict, List, Optional
  import numpy
  from pymc.backends import base
  from pymc.backends.base import MultiTrace
  from pymc.model import Model, modelcontext
label_desc: Use image node_id 9 for calling the NDArray obj's underlying member method code with example usage: obj.point(idx) and returns: unknown